Our client is an educational website owner who runs a business named trans neuron. He offers skills development courses to working professionals and students.Our client is an educational website owner who runs a business named trans neuron. He offers skills development courses to working professionals and students.To create an ML model that offers relevant suggestions based on students' and working professionals' requirements for courses and jobs, respectively.

Due to the emergence of a number of applications in the market, they needed a faster and guaranteed solution and majorly a cost-effective one. The solution was necessary as manual build and deployment could delay and create errors. We used DevOps to create an automated solution to test the application and deploy it automatically.

To begin, we needed to create a system that could fetch feed from the camera.After appropriate Research and Development, we opted for the OpenCV HAAR CASCADE algorithm as the means to detect faces.Additionally, the detection system is aligned with the task of recognizing the subscriber through image analysis to enable access to the web application.Lastly, we custom-trained our model with CNN of LSTM to classify Yoga Poses.

With most of the shopping activities moving online, the skincare industry is looking for ways to replicate the in-person shopping and suggestion system to garner people's trust and make appropriate recommendations that yield results for customer retention. We at MoogleLabs took on the challenge and created a system that can do exactly this through Artificial Intelligence and Machine Learning. To ensure that we were using the most credible sources, we took a significant chuck of initial data from Sephora and other resources to understand customers' needs as per the various demographic factors like skin texture, problems, etc. It helped us understand people's sentiments. Watch the video to understand the process we used to create the skincare recommendation system. As direct product recommendations can be too on the nose for some customers, our system makes ingredient recommendations for the clients. Then, they can choose the product they want to purchase with the appropriate active ingredient. Moreover, the current system is dynamic and flexible. So, it can incorporate new information to upgrade recommendations as further information gets fed into the system. The project offers scalability and can be changed to meet specific businesses' desires for specific products. Moreover, the same system can be applied to other industries to make further recommendations, like using the same procedure to make book recommendations per each individual's previous preferences and purchases.

Due to the increase in applications in the market, they needed a faster and guaranteed solution that was also cost-effective. The solution was necessary as manual build and deployment could delay and create errors. An automated solution was also necessary because of the hurdles in testing the application.

Creating unique solutions that far exceed the scalability and viability of traditional systems is now a reality thanks to the advancements in technologies like Artificial Intelligence and Machine Learning. One of the latest applications of the two technologies that our company was able to create includes the Face Recognition Attendance System. Companies can use the system to have accurate identification for attendance or security access.

We have carved out the solution to learn about the industry's fraud instances and boost the transformation of the education sector. The app has been widely used in different application domains, which include energy preservation, healthcare, e-commerce, social media, etc. The solution has included analyzing and mining certain types of data that include demographics, preferences, social interactions, and much more down the line. This has brought out the best. Such kinds of datasets include sensitive information, and it is majorly focused on risk reduction techniques only. Before, none of them has been successful in ensuring crypto security or user privacy with different techniques used till now. In order to fill the gap, blockchain technology has arrived as the most promising strategy or tactic. This all has been done so that there can be privacy preservation, not just due to security and privacy salient features but also because of resilience, adaptability, fault tolerance, and other reliable characteristics.